magali.detect_anomalies

Contents

magali.detect_anomalies#

magali.detect_anomalies(data, size_range, size_multiplier=2, num_scales=10, detection_threshold=0.5, overlap_ratio=0.5, border_exclusion=0)[source]#

Detect anomalies using blob detection.

Parameters:

  • data (xr.DataArray) – Input data array with coordinates “x” and “y”.

  • size_range (tuple) – Minimum and maximum size of detected anomalies in µm.

  • size_multiplier (int, optional) – Scaling factor for the detected blob sizes (default is 2).

  • num_scales (int, optional) – Number of sigma values for the blob detection (default is 10). A sigma value represents the scale or size of the blobs that the algorithm will detect. Smaller sigma values correspond to smaller blobs, while larger sigma values correspond to larger blobs.

  • detection_threshold (float, optional) – Detection threshold for the blob detection (default is 0.5). This parameter determines the sensitivity of the detection. A higher value means fewer blobs will be detected, and a lower value means more blobs will be detected.

  • overlap_ratio (float, optional) – Overlap fraction for merging blobs (default is 0.5).

  • border_exclusion (int, optional) – Border exclusion size in data units (default is 0). This parameter excludes blobs close to the border of the data array.

Returns:

bounding_boxes (list of lists) – Bounding boxes of detected anomalies in data coordinates. Each bounding box corresponds to a detected blob, defined by the coordinates and size of the blob.

Contents